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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/18496
Title: | Spatial modeling of rainfall trends using satellite datasets and geographic information system |
Other Titles: | Not Available |
Authors: | Sanjay Kumar Deepesh Machiwal Devi Dayal |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR::Central Arid Zone Research Institute |
Published/ Complete Date: | 2017-07-06 |
Project Code: | Not Available |
Keywords: | Rainfall Satellite dataset Trend Statistical test Geographic information system (GIS) |
Publisher: | Taylor & Francis |
Citation: | Not Available |
Series/Report no.: | Not Available; |
Abstract/Description: | This study developed a standard methodology for identifying rainfall spatial trends using satellite-based raster datasets, and demonstrated the methodology for Gujarat State of India where trends in seven rainfall series, i.e. annual, pre-monsoon, monsoon, post-monsoon, non-monsoon, monthly-maximum and one-day maximum, are investigated. It involves the novelty of exploring capabilities of geographic information system in implementing procedures of three trend tests, i.e. Spearman rank order correlation (SROC), Kendall rank correlation (KRC), and Mann-Kendall (MK) tests on the rainfall raster datasets of Tropical Rainfall Measurement Mission at 0.25°×0.25° resolution. Comparative evaluation of three tests revealed a fair agreement in of their test results in a major portion for pre-, post-, and non-monsoon and one-day maximum rainfall. Whereas, similar results of the KRC and MK tests are obtained over considerable area for annual, monsoon and monthly-maximum rainfall. This finding suggested that the importance of selection of the trend selecting appropriate tests may be according to depending on rainfall magnitudes at different chosen time scales, which and emphasizes robustness of the KRC and MK tests. The methodology can be adopted to investigate rainfall trends using raster satellite-datasets in other parts of the world. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Hydrological Sciences Journal |
NAAS Rating: | 8.19 |
Volume No.: | 62(10) |
Page Number: | 1636-1653 |
Name of the Division/Regional Station: | Regional Research Station, Kukma-Bhuj, Gujarat |
Source, DOI or any other URL: | 10.1080/02626667.2017.1304643 |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/18496 |
Appears in Collections: | NRM-CAZRI-Publication |
Files in This Item:
File | Description | Size | Format | |
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Kumar_et_al_rev_Krishi_Portal.pdf | 2.35 MB | Adobe PDF | View/Open |
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